Computers and Thought Award : Challenges of Massive Parallelism

Abstract

Artificial Intelligence has been the field of study for exploring the principles underlying thought, and utilizing their discovery to develop useful computers. Traditional AI models have been, consciously or subconsciously, optimized for available computing resources which has led AI in certain directions. The emergence of massively parallel computers liberates the way intelligence may be modeled. Although the AI community has yet to make a quantum leap, there are attempts to make use of the opportunities offered by massively parallel computers, such as memory-based reasoning, genetic algorithms, and other novel models. Even within the traditional AI approach, researchers have begun to realize that the needs for high performance computing and very large knowledge bases to develop intelligent systems requires massively parallel AI techniques. In this Computers and Thought Award lecture, I will argue that massively parallel artificial intelligence will add new dimensions to the ways that the AI goals are pursued, and demonstrate that massively parallel artificial intelligence is where AI meets the real world.